The Language Labyrinth: Constructive Critique on the Terminology Used in the AI Discourse
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Abstract (arXiv)
In the interdisciplinary field of artificial intelligence (AI) the problem of clear terminology is especially momentous. This paper claims, that AI debates are still characterised by a lack of critical distance to metaphors like 'training', 'learning' or 'deciding'. As consequence, reflections regarding responsibility or potential use-cases are greatly distorted. Yet, if relevant decision-makers are convinced that AI can develop an 'understanding' or properly 'interpret' issues, its regular use for sensitive tasks like deciding about social benefits or judging court cases looms. The chapter argues its claim by analysing central notions of the AI debate and tries to contribute by proposing more fitting terminology and hereby enabling more fruitful debates. It is a conceptual work at the intersection of critical computer science and philosophy of language.
Key facts. Cited by 5 papers in the map (data through 14 Oct 2026). Builds on 0 of its 37 references that are in the map. First posted on arXiv 18 Jul 2023.
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Citing papers per year: 2024: 1; 2025: 2; 2026: 2.
5 papers.
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- 2026Strategic Polysemy in AI Discourse: A Philosophical Analysis of Language, Hype, and Power22 Apr 2026
- 2026AI Narrative Breakdown. A Critical Assessment of Power and Promise29 Jan 2026
- 2025Rigor in AI: Doing Rigorous AI Work Requires a Broader, Responsible AI-Informed Conception of Rigor17 Jun 2025
- 2025How Large Language Models Are Changing MOOC Essay Answers: A Comparison of Pre- and Post-LLM Responses17 Apr 2025
- 2024"I Am the One and Only, Your Cyber BFF": Understanding the Impact of GenAI Requires Understanding the Impact of Anthropomorphic AI11 Oct 2024